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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
-tier machine learning and computer vision venues, actively participating in departmental seminars, and contributing to collaborative projects. Where to apply Website https://jobs.inria.fr/public/classic
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methods You will work closely with: - Dr. Martin Ramacher (machine learning for environmental applications) - Dr. Matthias Karl (urban air quality modelling and emissions) and collaborate within a project
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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energy systems and demand response; process and energy system modeling; optimization and model predictive control; and applications of artificial intelligence and machine learning to energy systems
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biosafety level 2 (BSL2+) lab), immunology (such as flow cytometry and CAR-T engineering), molecular biology (such as CRISPR, RNA biology), or animal models, (e) collaboration with other researchers both
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statistics, AI and machine learning methods, including demonstrated experience in analysing multiple global change drivers, e.g. land use intensity, climate change, nitrogen deposition. Proven capability
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research career. Research and technical training Training will include hands-on work in the following areas: Developing and validating deep-learning and machine-learning models using echocardiography
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genetically diverse mice under a multitude of conditions, and (3) develop multimodal machine learning models and methods to determine signatures and biomarkers to understand mechanisms distinguishing
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across a range of application areas, including education and healthcare. As these systems are increasingly deployed in high-stakes environments, there is a growing need for machine learning models
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | about 2 months ago
machine learning. Gathering this large panel of skills, the team aims at improving our understanding, reconstruction and forecasting of ocean dynamics, and more specifically to bridge model-driven and